Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Brain Imaging01:14

Brain Imaging

234
Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans),  magnetic resonance imaging (MRI),  functional magnetic resonance imaging (fMRI), and Transcranial Magnetic...
234
Depression: Overview01:18

Depression: Overview

252
Depression is a prevalent mental illness marked by persistent sadness and lack of interest in previously enjoyable activities. It can take several forms, including major depression, persistent depressive disorder, and bipolar I and II disorders. Symptoms range from emotional changes like chronic worry to physical changes like sleep disturbances and suicidal thoughts. From a neurobiological perspective, depression is believed to be triggered by abnormalities in the brain's prefrontal cortex,...
252

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Cognitive dysfunction associated with endocrine therapy and CDK4/6 inhibitors in breast cancer: A real-world analysis of the FDA Adverse Event Reporting System (FAERS) database.

Journal of geriatric oncology·2026
Same author

Aggregation-morphology-induced amplification and inversion of CPL in N-chiral substituted indolocarbazole derivatives.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy·2026
Same author

Smart single hollow magnetothermal nanorings with phase change materials for controlled drug release and negative MRI guided cancer therapy.

International journal of pharmaceutics·2026
Same author

The KDM-family inhibitor JIB-04 sensitizes AML cells to venetoclax by inducing a ferroptosis-like phenotype.

Blood neoplasia·2026
Same author

Visible-light-induced oxidant-free thiol-disulfide transformation.

Organic & biomolecular chemistry·2026
Same author

Protein 4.1R regulates CCDC26 and impacts myeloid leukemia progression.

Cellular signalling·2026

Related Experiment Video

Updated: Jul 9, 2025

Developing Neuroimaging Phenotypes of the Default Mode Network in PTSD: Integrating the Resting State, Working Memory, and Structural Connectivity
10:43

Developing Neuroimaging Phenotypes of the Default Mode Network in PTSD: Integrating the Resting State, Working Memory, and Structural Connectivity

Published on: July 1, 2014

15.1K

Connectomics-based resting-state functional network alterations predict suicidality in major depressive disorder.

Qing Wang1, Cancan He1, Zan Wang1,2

  • 1Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu, 210009, China.

Translational Psychiatry
|November 27, 2023
PubMed
Summary

Resting-state network (RSN) dysfunction in major depressive disorder (MDD) with suicidality was investigated. Abnormalities in brain network connectivity correlate with suicidality severity and may serve as diagnostic biomarkers for MDD patients.

More Related Videos

A Multimodal Imaging- and Stimulation-based Method of Evaluating Connectivity-related Brain Excitability in Patients with Epilepsy
08:23

A Multimodal Imaging- and Stimulation-based Method of Evaluating Connectivity-related Brain Excitability in Patients with Epilepsy

Published on: November 13, 2016

11.2K
Design and Implementation of an fMRI Study Examining Thought Suppression in Young Women with, and At-risk, for Depression
08:42

Design and Implementation of an fMRI Study Examining Thought Suppression in Young Women with, and At-risk, for Depression

Published on: May 19, 2015

10.7K

Related Experiment Videos

Last Updated: Jul 9, 2025

Developing Neuroimaging Phenotypes of the Default Mode Network in PTSD: Integrating the Resting State, Working Memory, and Structural Connectivity
10:43

Developing Neuroimaging Phenotypes of the Default Mode Network in PTSD: Integrating the Resting State, Working Memory, and Structural Connectivity

Published on: July 1, 2014

15.1K
A Multimodal Imaging- and Stimulation-based Method of Evaluating Connectivity-related Brain Excitability in Patients with Epilepsy
08:23

A Multimodal Imaging- and Stimulation-based Method of Evaluating Connectivity-related Brain Excitability in Patients with Epilepsy

Published on: November 13, 2016

11.2K
Design and Implementation of an fMRI Study Examining Thought Suppression in Young Women with, and At-risk, for Depression
08:42

Design and Implementation of an fMRI Study Examining Thought Suppression in Young Women with, and At-risk, for Depression

Published on: May 19, 2015

10.7K

Area of Science:

  • Neuroscience
  • Psychiatry
  • Medical Imaging

Background:

  • Major depressive disorder (MDD) poses significant risks, including suicidal behavior.
  • The dynamic alterations and network dysfunction in MDD patients with suicidality are not fully understood.
  • Investigating resting-state networks (RSNs) may reveal biomarkers for suicidality in MDD.

Purpose of the Study:

  • To investigate disturbances in RSNs among MDD patients with varying degrees of suicidal ideation and behavior.
  • To explore the potential of these RSN alterations as diagnostic biomarkers to differentiate MDD with and without suicidality.
  • To analyze the relationship between RSN connectivity, suicidality severity, and clinical factors.

Main Methods:

  • A multicenter, cross-sectional study involving 528 MDD patients and 998 healthy controls.
  • Construction and analysis of ten RSNs, including default mode (DMN), subcortical (SUB), ventral attention (VAN), and visual network (VIS).
  • Network-based statistical analysis and support vector machine (SVM) modeling to assess connectivity and discriminate patient groups.

Main Results:

  • Abnormalities in within- and between-network connectivity were observed, correlating with a 'suicidality gradient'.
  • Connectivity values showed complex patterns of increase and decrease with increasing suicidality.
  • SVM models achieved high accuracy (AUC 0.73-0.99) in distinguishing MDD patients based on suicidality gradients.

Conclusions:

  • Disrupted brain network connections are identified in MDD patients with varying suicidality.
  • These findings offer insights into the pathophysiological mechanisms underlying suicidality in MDD.
  • RSN alterations show promise as potential biomarkers for assessing suicidality in MDD.